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Hands-On Generative Adversarial Networks with Keras

Hands-On Generative Adversarial Networks with Keras: Your guide to implementing next-generation generative adversarial networks

By Rafael Valle
$29.99 $20.98
Book May 2019 272 pages 1st Edition
eBook
$29.99 $20.98
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$15.99 Monthly
eBook
$29.99 $20.98
Print
$43.99
Subscription
$15.99 Monthly

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Product Details


Publication date : May 3, 2019
Length 272 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781789538205
Category :
toc View table of contents toc Preview Book toc Download Code

Key benefits

  • Discover various GAN architectures using a Python and Keras library
  • Understand how GAN models function with the help of theoretical and practical examples
  • Apply your learnings to become an active contributor to open source GAN applications

Description

Generative Adversarial Networks (GANs) have revolutionized the fields of machine learning and deep learning. This book will be your first step toward understanding GAN architectures and tackling the challenges involved in training them. This book opens with an introduction to deep learning and generative models and their applications in artificial intelligence (AI). You will then learn how to build, evaluate, and improve your first GAN with the help of easy-to-follow examples. The next few chapters will guide you through training a GAN model to produce and improve high-resolution images. You will also learn how to implement conditional GANs that enable you to control characteristics of GAN output. You will build on your knowledge further by exploring a new training methodology for progressive growing of GANs. Moving on, you'll gain insights into state-of-the-art models in image synthesis, speech enhancement, and natural language generation using GANs. In addition to this, you'll be able to identify GAN samples with TequilaGAN. By the end of this book, you will be well-versed with the latest advancements in the GAN framework using various examples and datasets, and you will have developed the skills you need to implement GAN architectures for several tasks and domains, including computer vision, natural language processing (NLP), and audio processing. Foreword by Ting-Chun Wang, Senior Research Scientist, NVIDIA

What you will learn

Discover how GANs work and the advantages and challenges of working with them Control the output of GANs with the help of conditional GANs, using embedding and space manipulation Apply GANs to computer vision, natural language processing (NLP), and audio processing Understand how to implement progressive growing of GANs Use GANs for image synthesis and speech enhancement Explore the future of GANs in visual and sonic arts Implement pix2pixHD to turn semantic label maps into photorealistic images

What do you get with eBook?

Feature icon Instant access to your Digital eBook purchase
Feature icon Download this book in EPUB and PDF formats
Feature icon Access this title in our online reader with advanced features
Feature icon DRM FREE - Read whenever, wherever and however you want
Buy Now

Product Details


Publication date : May 3, 2019
Length 272 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781789538205
Category :

Table of Contents

14 Chapters
Preface Packt Packt
Section 1: Introduction and Environment Setup Packt Packt
Deep Learning Basics and Environment Setup Packt Packt
Introduction to Generative Models Packt Packt
Section 2: Training GANs Packt Packt
Implementing Your First GAN Packt Packt
Evaluating Your First GAN Packt Packt
Improving Your First GAN Packt Packt
Section 3: Application of GANs in Computer Vision, Natural Language Processing, and Audio Packt Packt
Progressive Growing of GANs Packt Packt
Generation of Discrete Sequences Using GANs Packt Packt
Text-to-Image Synthesis with GANs Packt Packt
TequilaGAN - Identifying GAN Samples Packt Packt
Whats next in GANs Packt Packt

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